Software ageing prediction using neural network with ridge

Since software systems become more complex than before, software ageing problems have a big impact on the performance of running software systems. To find software ageing in advance, some prediction methods were used to forecast those parameters which can indicate software ageing occurrences. Since the unsuitable parameters can reduce the prediction ability of an algorithm, in this study, multilayer perceptron (MLP) with ridge is proposed to improve the prediction accuracy of MLP and apply in software ageing problems. The proposed approach is a three‐step method. First, a pre‐processing process needs to be done by using outlier recognition, dispose, and normalisation. Second, MLP with ridge is proposed and used to optimise network structure. Third, a glowworm swarm optimisation method is utilised to automatically find optimal values of model parameters. In the experimental section, the results indicate that the proposed algorithm owns higher forecast accuracy than other state‐of‐the‐art methods on two levels.